Cited By
View all- Li JWang HKhan SLi QZomaya A(2013)A Fully Distributed Scheme for Discovery of Semantic RelationshipsIEEE Transactions on Services Computing10.1109/TSC.2012.166:4(457-469)Online publication date: 1-Oct-2013
FORUM: a flexible data integration system based on data semantics
Abstract
The FORUM project aims at extending existing data integration techniques in order to facilitate the development of mediation systems in large and dynamic environments. It is well known from the literature that a crucial point that hampers the development and wide adoption of mediation systems lies in the high entry and maintenance costs of such systems. To overcome these barriers, the FORUM project investigates three main research issues: (i) automatic discovery of semantic correspondences (ii) consistency maintenance of mappings, and (iii) tolerant rewriting of queries in the presence of approximate mappings.
References
[1]
F. N. Afrati, C. Li, and P. Mitra. Answering queries using views with arithmetic comparisons. In PODS, pages 209--220, 2002.
[2]
B. Alexe, M. Hernández, L.Popa, and W.C.Tan. Mapmerge: Correlating independent schema mappings. PVLDB, 3(1):81--92, 2010.
[3]
P. A. Bernstein, T. J. Green, S. Melnik, and A. Nash. Implementing mapping composition. VLDB J., 17(2):333--353, 2008.
[4]
N. Dalvi and D. Suciu. Answering queries from statistics and probabilistic views. In Proc. of VLDB 2005, pages 805--816. VLDB Endowment, 2005.
[5]
H. H. Do, S. Melnik, and E. Rahm. Comparison of schema matching evaluations. In IWWD, 2003.
[6]
F. Duchateau, Z. Bellahsene, and R. Coletta. A flexible approach for planning schema matching algorithms. In OTM Conferences, pages 249--264, 2008.
[7]
F. Duchateau, Z. Bellahsene, and M. Roche. A context-based measure for discovering approximate semantic matching between schema elements. In RCIS, 2007.
[8]
H. Jaudoin, P. Colomb, and O. Pivert. Ranking approximate query rewritings based on views. In Proc. of the 8th International Conference on Flexible Query Answering Systems (FQAS'09), pages 13--24, Roskilde, Denmark, 2009.
[9]
D. Knuth. Dancing links. Arxiv preprint cs.DS/0011047, 2000.
[10]
P. G. Kolaitis. Schema mappings, data exchange, and metadata management. In PODS '05: Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems, pages 61--75, New York, NY, USA, 2005. ACM.
[11]
C. Li and C. Clifton. Semantic integration in heterogeneous databases using neural networks. In VLDB, 1994.
[12]
J. Madhavan, P. A. Bernstein, and E. Rahm. Generic schema matching with cupid. In VLDB, pages 49--58, 2001.
[13]
T. Milo and S. Zohar. Using schema matching to simplify heterogeneous data translation. In VLDB, pages 122--133, 1998.
[14]
M. Murata, D. Lee, M. Mani, and K. Kawaguchi. Taxonomy of XML schema languages using formal language theory. ACM Trans. Internet Technol., 5(4):660--704, 2005.
[15]
R. Pottinger and A. Y. Levy. A scalable algorithm for answering queries using views. In VLDB, pages 484--495, San Francisco, CA, USA, 2000.
[16]
E. Rahm and P. A. Bernstein. A survey of approaches to automatic schema matching. VLDB J., 10(4):334--350, 2001.
[17]
R. Fagin, P. Kolaitis, R.Miller, and L.Popa. Data exchange:semantic and query answering. In Proc. ICDT 2003, 2003.
[18]
K. Saleem, Z. Bellahsene, and E. Hunt. PORSCHE: Performance ORiented SCHEma mediation. Information Systems - Elsevier, 33(7-8):637--657, 2008.
[19]
A. D. Sarma, X. Dong, and A. Halevy. Bootstrapping pay-as-you-go data integration systems. In Proc. of SIGMOD 2008, pages 861--874. ACM, 2008.
[20]
Secondstring. http://secondstring.sourceforge.net/, 2007.
[21]
P. Shvaiko and J. Euzenat. A survey of schema-based matching approaches. J. Data Semantics IV, pages 146--171, 2005.
[22]
Y. Velegrakis, R. Miller, and L. Popa. Preserving mapping consistency under schema changes. The VLDB Journal, 13(3):274--293, 2004.
[23]
Wordnet. http://wordnet.princeton.edu, 2007.
Recommendations
OPQL: A First OPM-Level Query Language for Scientific Workflow Provenance
SCC '11: Proceedings of the 2011 IEEE International Conference on Services ComputingProvenance, which is one kind of metadata that captures the derivation history of a data product, including its original data sources, intermediate products, and the steps that were applied to produce it, has become increasingly important in services ...
Editorial: OPQL: Querying scientific workflow provenance at the graph level
Provenance has become increasingly important in scientific workflows to understand, verify, and reproduce the result of scientific data analysis. Most existing systems store provenance data in provenance stores with proprietary provenance data models ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
Copyright © 2010 Authors.
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 06 December 2010
Published in SIGMOD Volume 39, Issue 2
Check for updates
Qualifiers
- Research-article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- View Citations1Total Citations
- 210Total Downloads
- Downloads (Last 12 months)1
- Downloads (Last 6 weeks)0
Reflects downloads up to 13 Dec 2024
Other Metrics
Citations
Cited By
View all- Li JWang HKhan SLi QZomaya A(2013)A Fully Distributed Scheme for Discovery of Semantic RelationshipsIEEE Transactions on Services Computing10.1109/TSC.2012.166:4(457-469)Online publication date: 1-Oct-2013
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in